Basic Statistics for Business and Economics with Student CD-ROM

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The Fifth Edition of Basic Statistics for Business and Economics is a shorter version of Lind/Marchal/Wathen's Statistical Techniques in Business and Economics, 12e. The authors of this text continue to provide a student-oriented approach to business statistics. In this book you will find step-by-step solved examples, realistic exercises, and up-to-date technology and illustrations. Book jacket.

What Is Statistics?

1

(22)

Introduction

2

(1)

Why Study Statistics?

2

(2)

What Is Meant by Statistics?

4

(2)

Types of Statistics

6

(3)

Descriptive Statistics

6

(1)

Inferential Statistics

7

(2)

Types of Variables

9

(1)

Levels of Measurement

9

(5)

Nominal-Level Data

10

(1)

Ordinal-Level Data

11

(1)

Interval-Level Data

12

(1)

Ratio-Level Data

12

(2)

Exercises

14

(1)

Statistics, Graphics, and Ethics

15

(3)

Misleading Statistics

15

(1)

Association Does Not Necessarily Imply Causation

15

(1)

Graphs Can Be Misleading

16

(1)

Become a Better Consumer and a Better Producer of Information

17

(1)

Ethics

17

(1)

Software Applications

18

(1)

Chapter Outline

19

(1)

Chapter Exercises

19

(1)

exercises.com

20

(1)

Dataset Exercises

21

(1)

Answers to Self-Review

22

(1)

Describing Data: Frequency Distributions and Graphic Presentation

23

(34)

Introduction

24

(1)

Constructing a Frequency Distribution

25

(4)

Class Intervals and Class Midpoints

29

(1)

A Software Example

29

(1)

Relative Frequency Distribution

30

(1)

Exercises

31

(1)

Graphic Presentation of a Frequency Distribution

32

(5)

Histogram

32

(2)

Frequency Polygon

34

(3)

Exercises

37

(4)

Cumulative Frequency Distributions

38

(3)

Exercises

41

(1)

Other Graphic Presentations of Data

42

(4)

Line Graphs

42

(1)

Bar Charts

43

(1)

Pie Charts

44

(2)

Exercises

46

(1)

Chapter Outline

47

(1)

Chapter Exercises

48

(5)

exercises.com

53

(1)

Dataset Exercises

53

(1)

Software Commands

54

(2)

Answers to Self-Review

56

(1)

Describing Data: Numerical Measures

57

(36)

Introduction

58

(1)

The Population Mean

59

(1)

The Sample Mean

60

(1)

Properties of the Arithmetic Mean

61

(1)

Exercises

62

(1)

The Weighted Mean

63

(1)

Exercises

64

(1)

The Median

64

(1)

The Mode

65

(2)

Exercises

67

(1)

Software Solution

68

(1)

The Relative Positions of the Mean, Median, and Mode

68

(2)

Exercises

70

(1)

The Geometric Mean

71

(1)

Exercises

72

(1)

Why Study Dispersion?

73

(1)

Measures of Dispersion

74

(2)

Range

74

(1)

Mean Deviation

75

(1)

Exercises

76

(3)

Variance and Standard Deviation

77

(2)

Exercises

79

(1)

Software Solution

80

(1)

Exercises

81

(1)

Interpretation and Uses of the Standard Deviation

82

(2)

Chebyshev's Theorem

82

(1)

The Empirical Rule

83

(1)

Exercises

84

(1)

Chapter Outline

84

(2)

Pronunciation Key

86

(1)

Chapter Exercises

86

(3)

exercises.com

89

(1)

Dataset Exercises

90

(1)

Software Commands

90

(2)

Answers to Self-Review

92

(1)

Describing Data: Displaying and Exploring Data

93

(27)

Introduction

94

(1)

Dot Plots

94

(2)

Exercises

96

(1)

Quartiles, Deciles, and Percentiles

97

(3)

Exercises

100

(1)

Box Plots

100

(2)

Exercises

102

(1)

Skewness

103

(4)

Exercises

107

(1)

Describing the Relationship between Two Variables

107

(3)

Exercises

110

(2)

Chapter Outline

112

(1)

Pronunciation Key

112

(1)

Chapter Exercises

112

(4)

exercises.com

116

(1)

Dataset Exercises

116

(1)

Software Commands

117

(2)

Answers to Self-Review

119

(1)

A Survey of Probability Concepts

120

(36)

Introduction

121

(1)

What Is a Probability?

122

(2)

Approaches to Assigning Probabilities

124

(3)

Classical Probability

124

(1)

Empirical Probability

125

(1)

Subjective Probability

126

(1)

Exercises

127

(1)

Some Rules for Computing Probabilities

128

(5)

Rules of Addition

128

(5)

Exercises

133

(4)

Rules of Multiplication

134

(3)

Contingency Tables

137

(2)

Tree Diagrams

139

(2)

Exercises

141

(1)

Principles of Counting

142

(4)

The Multiplication Formula

142

(1)

The Permutation Formula

143

(2)

The Combination Formula

145

(1)

Exercises

146

(1)

Chapter Outline

147

(1)

Pronunciation Key

148

(1)

Chapter Exercises

148

(4)

exercises.com

152

(1)

Dataset Exercises

152

(1)

Software Commands

153

(1)

Answers to Self-Review

154

(2)

Discrete Probability Distributions

156

(29)

Introduction

157

(1)

What Is a Probability Distribution?

157

(2)

Random Variables

159

(1)

Discrete Random Variable

159

(1)

Continuous Random Variable

160

(1)

The Mean, Variance, and Standard Deviation of a Probability Distribution

160

(3)

Mean

160

(1)

Variance and Standard Distribution'

161

(2)

Exercises

163

(1)

Binomial Probability Distribution

164

(6)

How Is a Binomial Probability Distribution Computed

165

(2)

Binomial Probability Tables

167

(3)

Exercises

170

(3)

Cumulative Binomial Probability Distributions

172

(1)

Exercises

173

(1)

Poisson Probability Distribution

174

(3)

Exercises

177

(1)

Chapter Outline

177

(1)

Chapter Exercises

178

(4)

Dataset Exercises

182

(1)

Software Commands

182

(2)

Answers to Self-Review

184

(1)

Continuous Probability Distributions

185

(26)

Introduction

186

(1)

The Family of Uniform Distributions

186

(3)

Exercises

189

(1)

The Family of Normal Probability Distributions

190

(3)

The Standard Normal Distribution

193

(3)

The Empirical Rule

195

(1)

Exercises

196

(3)

Finding Areas under the Normal Curve

197

(2)

Exercises

199

(3)

Exercises

202

(2)

Exercises

204

(1)

Chapter Outline

204

(1)

Chapter Exercises

205

(3)

Dataset Exercises

208

(1)

Software Commands

209

(1)

Answers to Self-Review

210

(1)

Sampling Methods and the Central Limit Theorem

211

(34)

Introduction

212

(1)

Sampling Methods

212

(6)

Reasons to Sample

212

(1)

Simple Random Sampling

213

(3)

Systematic Random Sampling

216

(1)

Stratified Random Sampling

216

(1)

Cluster Sampling

217

(1)

Exercises

218

(4)

Sampling ``Error''

220

(2)

Sampling Distribution of the Sample Mean

222

(3)

Exercises

225

(1)

The Central Limit Theorem

226

(6)

Exercises

232

(1)

Using the Sampling Distribution of the Sample Mean

233

(4)

Exercises

237

(1)

Chapter Outline

237

(1)

Pronunciation Key

238

(1)

Chapter Exercises

238

(4)

exercises.com

242

(1)

Dataset Exercises

243

(1)

Software Commands

243

(1)

Answers to Self-Review

244

(1)

Estimation and Confidence Intervals

245

(31)

Introduction

246

(1)

Point Estimates and Confidence Intervals

246

(7)

Known σ or a Large Sample

246

(5)

A Computer Simulation

251

(2)

Exercises

253

(7)

Unknown Population Standard Deviation and a Small Sample

254

(6)

Exercises

260

(1)

A Confidence Interval for a Proportion

260

(3)

Exercises

263

(1)

Finite-Population Correction Factor

263

(1)

Exercises

264

(1)

Choosing an Appropriate Sample Size

265

(2)

Exercises

267

(1)

Chapter Outline

268

(1)

Pronunciation Key

269

(1)

Chapter Exercises

269

(3)

exercises.com

272

(1)

Dataset Exercises

273

(1)

Software Commands

273

(2)

Answers to Self-Review

275

(1)

One-Sample Tests of Hypothesis

276

(36)

Introduction

277

(1)

What Is a Hypothesis?

277

(1)

What Is Hypothesis Testing?

278

(1)

Five-Step Procedure for Testing a Hypothesis

278

(5)

Step 1: State the Null Hypothesis (Ho) and the Alternate Hypothesis (H1)

278

(1)

Step 2: Select a Level of Significance

279

(1)

Step 3: Select the Test Statistic

279

(2)

Step 4: Formulate the Decision Rule

281

(1)

Step 5: Make a Decision

282

(1)

One-Tailed and Two-Tailed Tests of Significance

283

(1)

Testing for a Population Mean with a Known Population Standard Deviation

284

(4)

A Two-Tailed Test

284

(4)

A One-Tailed Test

288

(1)

p-Value in Hypothesis Testing

288

(2)

Testing for a Population Mean: Large Sample, Population Standard Deviation Unknown

290

(1)

Exercises

291

(1)

Tests Concerning Proportions

292

(3)

Exercises

295

(1)

Testing for a Population Mean: Small Sample, Population Standard Deviation Unknown

295

(5)

Exercises

300

(3)

A Software Solution

301

(2)

Exercises

303

(1)

Chapter Outline

304

(1)

Pronunciation Key

305

(1)

Chapter Exercises

305

(4)

exercises.com

309

(1)

Dataset Exercises

309

(1)

Software Commands

310

(1)

Answers to Self-Review

311

(1)

Two-Sample Tests of Hypothesis

312

(32)

Introduction

313

(1)

Two-Sample Tests of Hypothesis: Independent Samples

313

(5)

Exercises

318

(1)

Two-Sample Tests about Proportions

319

(2)

Exercises

321

(2)

Comparing Population Means with Small Samples

323

(3)

Exercises

326

(1)

Two-Sample Tests of Hypothesis: Dependent Samples

327

(4)

Comparing Dependent and Independent Samples

331

(2)

Exercises

333

(1)

Chapter Outline

334

(1)

Pronunciation Key

335

(1)

Chapter Exercises

335

(5)

exercises.com

340

(1)

Dataset Exercises

341

(1)

Software Commands

341

(1)

Answers to Self-Review

342

(2)

Analysis of Variance

344

(30)

Introduction

345

(1)

The F Distribution

345

(1)

Comparing Two Population Variances

346

(3)

Exercises

349

(1)

Anova Assumptions

350

(2)

The Anova Test

352

(7)

Exercises

359

(1)

Inferences about Pairs of Treatment Means

360

(2)

Exercises

362

(2)

Chapter Outline

364

(1)

Pronunciation Key

365

(1)

Chapter Exercises

365

(5)

exercises.com

370

(1)

Dataset Exercises

370

(1)

Software Commands

371

(2)

Answers to Self-Review

373

(1)

Linear Regression and Correlation

374

(47)

Introduction

375

(1)

What Is Correlation Analysis?

375

(2)

The Coefficient of Correlation

377

(4)

The Coefficient of Determination

381

(1)

Correlation and Cause

382

(1)

Exercises

382

(2)

Testing the Significance of the Correlation Coefficient

384

(2)

Exercises

386

(1)

Regression Analysis

386

(4)

Least Squares Principle

386

(3)

Drawing the Line of Regression

389

(1)

Exercises

390

(2)

The Standard Error of Estimate

392

(3)

Assumptions Underlying Linear Regression

395

(1)

Exercises

396

(1)

Confidence and Prediction Intervals

396

(4)

Exercises

400

(1)

More on the Coefficient of Determination

400

(3)

Exercises

403

(1)

The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimate